A Slippery Slope: How Synthetic Identities Can Slip Through Your Defenses

Synthetic fraud, involving manipulated or entirely fabricated identities, has evolved from rapid credit-card and mobile-device schemes into longer-term “bust-out” activity affecting credit, auto finance, and, increasingly since COVID-19, bank and fintech deposit accounts. The passage argues that many institutions fail to detect it because they rely on Customer Identification Program checks and credit-bureau data that may themselves contain synthetic identities, while also using unsuitable follow-up verification methods that can validate fraudulent credit profiles. It emphasizes that synthetic-fraud detection requires specialized analytics capable of distinguishing manipulated from fabricated identities, alongside separate controls for third-party, first-party, and synthetic fraud at account opening. Deposit providers are described as particularly exposed because their direct per-account losses may appear lower than those of card issuers or auto lenders, even though fraudulent accounts can facilitate scams, money laundering, benefits fraud, and other crimes. The piece attributes much of the problem to limited industry education and promotes Socure’s Sigma Synthetic Fraud product as a machine-learning-based solution for identifying synthetic identities at origination and within existing customer portfolios.

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